1 रिपॉजिटरी
Awesome GitHub RepositoriesDeclarative Machine Learning Frameworks
Frameworks that enable the specification of model architectures and training pipelines via configuration files instead of code.
Distinct from Machine Learning Training: Existing candidates focus on training loops or generic training, not the specific declarative paradigm of avoiding manual code.
Explore 1 awesome GitHub repository matching artificial intelligence & ml · Declarative Machine Learning Frameworks. Refine with filters or upvote what's useful.
Awesome Declarative Machine Learning Frameworks GitHub Repositories
AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
- uber/ludwig
uber/ludwig
11,718GitHub पर देखेंLudwig is a declarative machine learning framework designed for training neural networks and large language models using configuration files instead of manual coding. It functions as a multimodal model builder and a low-code tool for supervised fine-tuning, allowing users to build models that process mixed inputs of text, images, audio, and tabular data. The project distinguishes itself through an automated hyperparameter optimizer and a system for large language model fine-tuning using parameter-efficient adapters. It features a multimodal data pipeline and the ability to automatically gener
Provides a framework for building and training neural networks using declarative configuration files instead of manual coding.
Python
